Jose Patino

Artificial Intelligence · 2020–2022

A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jose Patino trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Jee-weon Jung
  2. Jimmy Ba
  3. Arsha Nagrani
  4. Xin Eric Wang
  5. Geoffrey E. Hinton
  6. Massimiliano Todisco
  7. Yoshua Bengio
  8. David Snyder
  9. Junichi Yamagishi
  10. Andrew Zisserman

Papers from Jose Patino's perspective

Ordered by how strongly the researchers Jose Patino trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Attention is All you Need (Neural Information Processing Systems)
  4. Layer Normalization
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers